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An efficient watermarking technique for tamper detection and localization of medical images

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Abstract

With the exponential rise of multimedia technology and networked infrastructure, electronic healthcare is coming up a big way. One of the most important challenges in an electronic healthcare setup is the authentication of medical images, received by an expert at a far-off location from the sender. With an aim to address the critical authentication issue, this paper presents a fragile watermarking technique capable of tamper detection and localization in medical/general images. We divide the cover image into 4 × 4 non overlapping pixel blocks; with each block further sub-divided into two 4 × 2 blocks, called as Upper Half Block (UHB) and Lower Half Block (LHB). The information embedded in LHB facilitates tamper detection while as that embedded in UHB facilities tamper localization. The experimental results show that, in addition to tamper detection and localization capability, the proposed technique has lesser computational complexity when compared to other state-of-art techniques. Further, the proposed scheme results in average PSNR of 51.26 dB for a payload of one bit per pixel (1bpp) indicating that the watermarked images obtained are of high visual quality.

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Acknowledgements

The authors would like to thank the Department of Science and Technology (DST) New Delhi, Government of India for providing financial support under DST Inspire Fellowship Scheme.

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Authors and Affiliations

  1. Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar, India

    Solihah Gull, Nazir A. Loan, Shabir A. Parah & Javaid A. Sheikh

  2. Department of Electronics Engineering, Institute of Technology, Zakoora, Srinagar, India

    G. M. Bhat

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  1. Solihah Gull
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  2. Nazir A. Loan
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  3. Shabir A. Parah
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  4. Javaid A. Sheikh
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  5. G. M. Bhat
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Correspondence to Shabir A. Parah.

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Gull, S., Loan, N.A., Parah, S.A. et al. An efficient watermarking technique for tamper detection and localization of medical images. J Ambient Intell Human Comput 11, 1799–1808 (2020). https://doi.org/10.1007/s12652-018-1158-8

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  • DOI: https://doi.org/10.1007/s12652-018-1158-8

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